As clinical SARS-CoV-2 surveillance programs are being reduced, wastewater-based epidemiology (WBE) has emerged as a promising alternative for monitoring viral circulation. However, large-scale validation of wastewater sequencing against clinical data across multiple lineages and geographic regions remains limited. This study aimed to evaluate the concordance between wastewater and clinical SARS-CoV-2 lineage surveillance at a national scale and assess patterns of lineage emergence and geographic spread. From September 11, 2023, to April 1, 2025, we collected 3,151 wastewater samples from 42 treatment plants across 28 U.S. states. Samples underwent tiled amplicon sequencing using ARTIC V5.3.2 primers, with lineage abundance estimated using Freyja. We compared wastewater lineage proportions to CDC clinical surveillance data using Spearman rank correlation coefficients and analyzed temporal patterns of lineage emergence and geographic distribution. Wastewater lineage abundances showed strong positive correlations with clinical data across all major Pango lineages, with Spearman coefficients ranging from 0.46 (Omicron BA) to 0.94 (Omicron XEC), all statistically significant ( p < 0.05 after Bonferroni correction). Wastewater surveillance captured the succession pattern from Omicron XBB/HV/FL/EG lineages to JN (reaching 90% by February 2024), followed by KP emergence (majority by June 2024), and the recent appearance of XEC and LP lineages. Geographic analysis revealed substantial variation in lineage spread, with emergence times differing by over 200 days between first and last detection sites for some lineages. Only Omicron XBB emerged in all surveyed sites, while other lineages showed more limited geographic distribution. Wastewater sequencing provides reliable, population-level surveillance of SARS-CoV-2 lineages that closely mirror clinical data, while offering advantages such as rapid processing, unbiased sampling, and broad geographic coverage. As clinical surveillance capacity declines, wastewater monitoring represents a cost-effective approach for tracking lineage emergence and spread, with potential applications for other respiratory pathogens.
Zulli et al. (Fri,) studied this question.